Update app.py

app.py

@@ -56,7 +56,7 @@ load_dotenv()
 
 # langfuse analytics
 from langfuse.callback import CallbackHandler
-from langchain.callbacks import BaseCallbackHandler
+
 # Inventory API data table
 from tabulate import tabulate
 
@@ -121,13 +121,6 @@ branch = os.getenv("branch")
 langfuse_handler = CallbackHandler()
 langfuse_handler.auth_check()  # Optional: Checks if the authentication is successful
 
-# Create the callback manager and add both the response history and langfuse handler
-callback_handler = ResponseHistoryCallback()
-
-
-
-
-
 nltk.download('punkt')
 
 open_api_key_token = os.getenv("OPENAI_API_KEY")
@@ -163,18 +156,7 @@ apis = [
 # LLM setup
 llm = ChatOpenAI(model="gpt-4o-mini", max_tokens=300, temperature=0.1)
 llm_chart = OpenAI(is_safe=False)
-# Define a custom callback to capture responses and track history
-class ResponseHistoryCallback(BaseCallbackHandler):
-    def __init__(self):
-        self.history = []  # Initialize history to store responses
-
-    def on_agent_finish(self, output):
-        # Capture the response when the agent finishes
-        self.history.append(output)
-        print(f"Agent's response: {output}")  # Optionally print
-
-    def get_history(self):
-        return self.history  # Return the captured history
+
 def get_schema(_):
     schema_info = db.get_table_info()  # This should be a string of your SQL schema
     return schema_info
@@ -521,7 +503,7 @@ def chat_with_llm(df,question):
 def bind_llm(llm, tools,prompt_template):
     llm = llm.bind()
     agent = create_tool_calling_agent(llm, tools, ChatPromptTemplate.from_template(prompt_template))
-    agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True, max_iterations=3)
+    agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
     return agent_executor
 
 # Define input and output models using Pydantic
@@ -592,10 +574,8 @@ def handle_query(user_question, chatbot, audio=None):
     Function to handle the processing of user input with `AgentExecutor.invoke()`.
     
     global current_event, stop_event
-
     # Clear previous stop event and current_event
     stop_event.clear()
-
     if current_event and not current_event.done():
         chatbot.append(("","A query is already being processed. Please stop it before starting a new one."))
         return gr.update(value=chatbot)
@@ -617,7 +597,6 @@ def handle_query(user_question, chatbot, audio=None):
             return gr.update(value=chatbot)
             
         time.sleep(1)  # Wait for 1 second before checking again
-
     if current_event.cancelled():
         chatbot.append((user_question, "Sorry, we encountered an error while processing your request. Please try after some time."))
         return gr.update(value=chatbot)
@@ -691,7 +670,6 @@ def answer_question_thread(user_question, chatbot,audio=None):
      
     global iterations
     iterations = 0
-    agent_responses = []
     # Ensure the temporary chart directory exists
     # ensure_temp_chart_dir()
     # Clean the /tmp/gradio/ directory
@@ -709,7 +687,6 @@ def answer_question_thread(user_question, chatbot,audio=None):
         with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_audio_file:
             audio_segment.export(temp_audio_file.name, format="wav")
             temp_audio_file_path = temp_audio_file.name
-
         recognizer = sr.Recognizer()
         with sr.AudioFile(temp_audio_file_path) as source:
             audio_content = recognizer.record(source)
@@ -723,11 +700,7 @@ def answer_question_thread(user_question, chatbot,audio=None):
 
     while iterations < max_iterations:
 
-        #response = agent_executor.invoke({"input": user_question}, config={"callbacks": [langfuse_handler]}, early_stopping_method="generate")
-        response = agent_executor.invoke({"input": user_question}, config={"callbacks": [[callback_handler, langfuse_handler]]}, early_stopping_method="generate")
-        # Track the response
-        agent_responses.append(response)
-        
+        response = agent_executor.invoke({"input": user_question}, config={"callbacks": [langfuse_handler]}, early_stopping_method="generate")
         #create_file_HF()
         if isinstance(response, dict):
             response_text = response.get("output", "")
@@ -736,12 +709,9 @@ def answer_question_thread(user_question, chatbot,audio=None):
         if "invalid" not in response_text.lower():
             break
         iterations += 1
-        print("iterations::")
-        print(iterations)
-        if iterations == max_iterations:
-            print("final response::")
-            print(response)
-            return user_question , "Sorry, I couldn't complete your request" #"The agent could not generate a valid response within the iteration limit."
+
+    if iterations == max_iterations:
+        return user_question , "Sorry, I couldn't complete your request" #"The agent could not generate a valid response within the iteration limit."
 
     if os.getenv("IMAGE_PATH") in response_text:
         # Open the image file
@@ -780,20 +750,9 @@ def answer_question_thread(user_question, chatbot,audio=None):
             except Exception as e:
                 print(f"Error loading image file: {e}")
                 response_text =  "Chart generation failed. Please try again."
-        if("max iterations" in response_text):
-            print("max iterations error in 1")
-            if agent_executor.history:
-                print(agent_executor.history[-1])
-                #return agent_executor.history[-1].get("output")
-                
+
         return user_question, response_text
     else:
-        if("max iterations" in response_text):
-            print("max iterations error in 2")
-            # Access the response history after execution
-            response_history = callback_handler.get_history()
-            print("Response History:", response_history)
-
         return user_question, response_text
     # response_text = response_text.replace('\n', ' ').replace('  ', ' ').strip()
     # return response_text
@@ -830,7 +789,7 @@ def answer_question(user_question, chatbot, audio=None):
             user_question = "Sorry, I could not understand the audio."
         except sr.RequestError:
             user_question = "Could not request results from Google Speech Recognition service."
-  
+
     while iterations < max_iterations:
 
         response = agent_executor.invoke({"input": user_question}, config={"callbacks": [langfuse_handler]})
@@ -1262,19 +1221,13 @@ def handle_large_dataset(df, create_document,isDataFrame):
         if len(df.columns) > 1:
                 # Skipping the original first column
                 # List of required columns
-                
                 required_columns = ['BROKER', 'ACCOUNT NUMBER', 'EMPLOYEE NAME', 'ACCOUNT NAME', 'ACCOUNT ID']
                 # Filter the DataFrame to include only the required columns
                 #print(df[required_columns])
                 #limited_data = df[required_columns]
-                limited_data_top3 = df.head(3)
-                if len(df.columns) > 5:
-                    limited_data = limited_data_top3[required_columns]
-                    limited_data_without_first_column = limited_data.iloc[:, 1:] 
-                else:
-                    limited_data_without_first_column = limited_data_top3
-                
-                
+                limited_data11 = df.head(3)
+                limited_data = limited_data11[required_columns]
+                limited_data_without_first_column = limited_data.iloc[:, 1:] 
         else:
                 limited_data = df.head(20)
                 limited_data_without_first_column = limited_data 
@@ -1382,14 +1335,11 @@ def create_pdf(cname,ename,account_number, directory):
         output.write(filled.read())
 
     """from PyPDF2 import PdfReader, PdfWriter
-
     reader = PdfReader(output_file_name)
     writer = PdfWriter()
-
     for page in reader.pages:
         page.merge_page(page)  # Flatten content
         writer.add_page(page)
-
     with open(output_file_name, "wb") as f:
         writer.write(f)
     """
@@ -1438,7 +1388,6 @@ def get_download_link(file_path,file_name):
     return f"{base_url}/{file_path}/{file_name}"
 
 css = """
-
 /* Example of custom button styling */
 .gr-button {
     background-color: #6366f1; /* Change to your desired button color */
@@ -1449,11 +1398,9 @@ css = """
     font-size: 12px;
     cursor: pointer;
 }
-
 .gr-button:hover {
     background-color: #8a92f7; /* Darker shade on hover */
 }
-
 .gr-buttonbig {
     background-color: #6366f1; /* Change to your desired button color */
     color: white;
@@ -1463,41 +1410,33 @@ css = """
     font-size: 14px;
     cursor: pointer;
 }
-
 .gr-buttonbig:hover {
     background-color: #8a92f7; /* Darker shade on hover */
 }
-
 /* Customizing the Logout link to be on the right */
 .logout-link {
     text-align: right;
     display: inline-block;
     width: 100%;
 }
-
 .logout-link a {
     color: #4A90E2; /* Link color */
     text-decoration: none;
     font-size: 16px;
 }
-
 .chatbot_gpt {
     height: 600px !important; /* Adjust height as needed */
 }
-
 .logout-link a:hover {
     text-decoration: underline; /* Underline on hover */
 }
-
 .message-buttons-right{
     display: none !important; 
 }
-
 body, .gradio-container {
     margin: 0;
     padding: 0;
 }
-
 /* Styling the tab header with a blue background */
 .gr-tab-header {
     background-color: #4A90E2; /* Blue background for the tab header */
@@ -1506,17 +1445,14 @@ body, .gradio-container {
     color: white;
     font-size: 16px;
 }
-
 /* Styling the selected tab text color to be green */
 .gr-tab-header .gr-tab-active {
     color: green; /* Change selected tab text to green */
 }
-
 /* Keep non-selected tab text color white */
 .gr-tab-header .gr-tab {
     color: white;
 }
-
 /* Custom CSS for reducing the size of the video element */
 .video-player {
     width: 500px;  /* Set a custom width for the video */
@@ -1528,7 +1464,6 @@ body, .gradio-container {
     width:500px;
     justify-content: flex-start; /* Align buttons to the left */
     gap: 10px; /* Space between buttons */
-
 }
 .custom-button {
     width: 100px; /* Small width */
@@ -1541,7 +1476,6 @@ body, .gradio-container {
     border-radius: 5px; /* Rounded corners */
     cursor: pointer; /* Pointer cursor on hover */
 }
-
 .custom-button:hover {
     background-color: #e0e0e0; /* Background color on hover */
 }
@@ -1620,4 +1554,4 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
     u.upload(lambda _: (gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)), None, [title_textbox, summary_textarea, add_button])
 
     
-demo.launch(auth=[("lakshmi", "redmind"), ("admin", "redmind"), ("arun", "redmind"), ("NewageGlobal", "Newage123$")], auth_message="RedMindGPT", inline=False)
+demo.launch(auth=[("lakshmi", "redmind"), ("admin", "redmind"), ("arun", "redmind"), ("NewageGlobal", "Newage123$")], auth_message="RedMindGPT", inline=False)